CSIRO Data61 PhD scholarship: Deep Neural Networks Reliability Analytics

Summary

Enrolment status New students
Student type Domestic students, International students
Level of study Higher Degree by Research
Study area Engineering and Computing
HDR funding type Living stipend scholarship
Scholarship value This scholarship is provided by the CSIRO/Data61 for three years (with a possible 6 months extension) for a PhD. After the EOI stage, the student will work with UQ and Data61 researchers towards the application of a UQ RTP and/or CSIRO’s Data61 PhD scholarship/top up, subject to eligibility criteria and an evaluation by an independent assessment committee.
Opening date 27 May 2020
Closing date 29 June 2020

Description

Advanced cyber attacks and cyber threats have the power of mutating and outbreaking faster than the response of current detection models that are based on artificial intelligent and Big Data analytics. Digital competitiveness of any organization thus desires high-quality large datasets and their innovative use.

This project will contribute to the quality of the collected data for data analytics. While machine learning and deep learning are increasingly adopted in helping decision making in various areas, their reliability is still an open question, as machine learning and deep learning are normally black-box approaches. This project aims to investigate the quality of the data collected and their influence on the data analytics using approaches like generative adversarial networks and investigate the security and reliability of the machine learning and deep learning modules via testing and formal analysis. Various big data techniques will be studied, benchmarked and adapted to enable reliable data analytics. 

This is a prestigious PhD scholarship supervised by both UQ and Data61 researchers. We invite anyone who is interested in security analytics to be part of this project as a PhD. The PhD application will follow this process:

  1. EOI to UQ (see How to Apply)
  2. Acceptance as preferred candidate and invitation to submit full application to UQ PhD programme
  3. Acceptance as UQ candidate and interview with UQ and Data61 supervisors
  4. Application for Data61 scholarships
  5. Acceptance and commencement of PhD scholarships.

Working with leading researchers from UQ Cyber Security and CSIRO’s Data61, the PhD student will gain access to state-of-the-art equipment through UQ’s cyber security facilities and groups, Data61’s facilities, UQ Energy Testlab, and specific domain expertise through collaboration with other research groups at ITEE.

Eligibility

To be eligible, you must meet the entry requirements for a higher degree by research.

Applications are closed.

Before you get started

If this scholarship has rules, download and read them.

How to apply

To be considered for this scholarship, please email the following documents (in PDF) to Professor Ryan Ko (r.ko@uq.edu.au) with the subject heading: EOI for UQ-Data61 CRP Project Deep Neural Networks Reliability Analytics

  • Cover letter
  • CV
  • Academic transcript/s
  • Names of two referees who can comment on your ability to undertake in-depth research. Referee reports are carefully assessed with your application.

Guide for CVs:

Your CV provides an overview of your educational and employment history and your skills. You should include:

Educational history

List all degrees studied in your educational history, indicating the name of the degree, university, years studied and GPA if known. If you completed a thesis as part of your degree, provide its title, the mark and list your supervisor/s.

Employment history

List your employer, your role, duration of employment, duties and achievements.

Awards

List any awards received throughout your tertiary study or employment.

Publications/Papers

Provide a list of publications that have been accepted or published. Do not list publications that are submitted. Do not attach publications/papers to your application. 

Other information

You may provide other information in the CV that you think is relevant to your assessment, for example, information about research interests, research project experience, or key skills such as coding. 

Guide for Academic Transcripts

Provide official transcripts for all university studies as pdf documents, including degrees not completed or abandoned. Provide translated documents where transcripts are in a language other than English. Ensure scans are legible.

  • Do not provide transcripts from high school.
  • Do not provide testamurs/degree certificates.
  • Do not provide award certificates.

Additional Documents

Awards

Do not provide evidence of awards, for example certificates. All awards should be listed in the CV.

Publications

If you have publications, you may provide a list of all publications in your CV, in order of most current to beyond. Provide a web link to view publications and do not attach publications/papers.

Do not attach your Masters or Honours thesis.

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission to both UQ and Data61. You can familiarise yourself with the documents required for this process on the Future Student's website.

Selection criteria

To be eligible, you must meet the entry requirements for a higher degree by research.

Applications are closed.

Contact

Professor Ryan Ko
+61 7 3365 1092
Applications are closed.

Terms and conditions

Read the policy on UQ Research Scholarships.

A domestic part-time student with carer’s responsibilities, a medical condition or a disability, which prevents them from studying full time may be eligible for scholarship consideration, on a case by case basis.

Applications are closed.